Arctic Soil Governs Whether Climate Change Drives Global Losses or Gains in Soil Carbon
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Perennial vegetation with high plant diversity, e.g., restored prairie, is known for stimulation of soil carbon (C) gains, due in part to enhanced formation of pore structure beneficial for long-term C storage. However, the prevalence of this phenomenon across soils of different types remains poorly understood. The aim of the study was to assess the associations between pore structure, soil C, and their differences in monoculture switchgrass and polyculture restored prairie vegetation across a wide range of soils dominating the Upper Midwest of the USA. Six experimental sites were sampled, representing three soil types with texture ranging from sandy to silt loams. The two vegetation systems studied at each site were (i) monoculture switchgrass (Panicum virgatum L.), and (ii) polyculture restored prairie, also containing switchgrass as one of its species. X-ray computed micro-tomography (µCT) was employed to analyze soil pore structure. Structural equation modeling and multiple path analyses were used to assess direct and indirect effects of soil texture and pore characteristics on microbial biomass C (MBC), particulate organic matter (POM), dissolved organic C (DOC), short-term respiration (CO 2 ), and, ultimately, soil organic C (SOC). Across studied sites, prairie increased fractions of medium (50–150 µm Ø) pores by 11–45 %, SOC by 3–69 %, and MBC by 18–59 % (except for one site). The greater were the prairie-induced increases in the medium pore volumes, the greater were the prairie-induced SOC gains. Greater C losses via CO 2 and DOC contributed to slower C accumulation in the prairie soil. We surmise that the interactive feedback loop relating medium pores and soil C acts across a wide range of soil textures and is an important mechanism through which perennial vegetation with high plant diversity, such as restored prairie, promotes rapid SOC gains.
Quantifying changes in soil organic carbon (SOC) stocks and other soil properties is essential for understanding how soils will respond to land management practices and global change. Although they are widely used, comparisons of SOC stocks at fixed depth (FD) intervals are subject to errors when changes in bulk density or soil organic matter occur. The equivalent soil mass (ESM) method has been recommended in lieu of FD for assessing changes in SOC stocks in mineral soils, but ESM remains underutilized for SOC stocks and has rarely been used for other soil properties. In this paper, we draw attention to the limitations of the FD method and demonstrate the advantages of the ESM approach. We provide illustrations to show that the FD approach is susceptible to errors not only for quantifying SOC stocks but also for soil mass-based properties such as SOC mass percent, C:N mass ratio, and δ 13 C. Here we describe the ESM approach and show how it mitigates the FD method limitations. Using bulk density change simulations applied to an empirical dataset from bioenergy cropping systems, we show that the ESM method provides consistently lower errors than FD when quantifying changes in SOC stocks and other soil properties. To simplify the use of ESM, we detail how the method can be integrated into sampling schemes, and we provide an example R computer script that can perform ESM calculations on large datasets. We encourage future studies, whether temporal or comparative, to utilize sampling methods that are amenable to the ESM approach. Overall, we agree with previous recommendations that ESM should be the standard method for evaluating SOC stock changes in mineral soils, but we further suggest that ESM may also be preferred for comparisons of other soil properties including mass percentages, elemental mass ratios, and stable isotope composition.
Abstract Soil is the largest terrestrial reservoir of organic carbon and is central for climate change mitigation and carbon-climate feedbacks. Chemical and physical associations of soil carbon with minerals play a critical role in carbon storage, but the amount and global capacity for storage in this form remain unquantified. Here, we produce spatially-resolved global estimates of mineral-associated organic carbon stocks and carbon-storage capacity by analyzing 1144 globally-distributed soil profiles. We show that current stocks total 899 Pg C to a depth of 1 m in non-permafrost mineral soils. Although this constitutes 66% and 70% of soil carbon in surface and deeper layers, respectively, it is only 42% and 21% of the mineralogical capacity. Regions under agricultural management and deeper soil layers show the largest undersaturation of mineral-associated carbon. Critically, the degree of undersaturation indicates sequestration efficiency over years to decades. We show that, across 103 carbon-accrual measurements spanning management interventions globally, soils furthest from their mineralogical capacity are more effective at accruing carbon; sequestration rates average 3-times higher in soils at one tenth of their capacity compared to soils at one half of their capacity. Our findings provide insights into the world’s soils, their capacity to store carbon, and priority regions and actions for soil carbon management.
Soil organic carbon (SOC) is an important metric of soil health and the terrestrial carbon balance. Short‐term climate variations affect SOC through changes in temperature and moisture, which control vegetation growth and soil decomposition. We evaluated a satellite data‐driven carbon model, operating under the NASA Soil Moisture Active‐Passive (SMAP) mission, as a means of monitoring global surface SOC dynamics. The SMAP Level 4 Carbon (L4C) product estimates a daily global carbon budget including surface (0‐ to 5‐cm depth) SOC. We found that the L4C mean latitudinal SOC distribution is generally consistent with alternative assessments from static soil inventory records and dynamic global vegetation models (r ≥ 0.89). Within forest systems, based on inventory data, L4C SOC is most similar in magnitude to litterfall but is correlated with coarse woody debris ( urn:x-wiley:jgrg:media:jgrg21790:jgrg21790-math-0001) and total SOC ( urn:x-wiley:jgrg:media:jgrg21790:jgrg21790-math-0002). L4C SOC is sensitive to seasonal and annual climate variability, with mean residence times that range from 1.5 years in the wet tropics to 17 years in the cold tundra. Incorporating soil moisture retrievals from the SMAP L‐band (1.4 GHz) microwave radiometer within the L4C algorithm provides enhanced soil moisture sensitivity under low‐to‐moderate vegetation cover (<5 kg/sq.m vegetation water content). The L‐band soil moisture had the greatest impact on the L4C carbon budget in semiarid regions, which span almost 60% of the globe and account for substantial variability in the terrestrial carbon sink. The L4C operational product enables prognostic investigations into effects of recent climate trends and anomalies (e.g., droughts and pluvials) on shallow soil carbon dynamics.
This dataset contains model output and input data, as well as source code examples for the Terrestrial Ecosystem Model with the Dynamic Vegetation Model and Dynamic Organic Soil (DVM-DOS-TEM) for the field sites Imnavait creek and the Bonanza creek Long Term Ecological Research Network (LTER). The data covers simulations from the last glacial maximum (LGM) until 2100 for a selection of paleo scenarios, setting the mean temperature of the LGM up to 10°C lower than pre-industrial conditions. The model structure was modulated to represent various model versions, and this dataset contains the relevant changes in the source code. The raw output data, the processed statistical data, the setup and processing scripts as well as parameter value distribution files from a parameter sensitivity analysis are included as well. Model outputs include active layer depth, organic soil carbon, soil layer depths, gross primary productivity (GPP) with and without nitrogen limitation, net primary productivity (NPP), soil liquid water content, heterotrophic, maintenance, and growth respiration, soil temperature, and vegetation carbon (*.nc files). The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research.Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.
Soil stores more carbon (C) than all vegetation and the atmosphere combined. Soil C stocks are broadly shaped by temperature, moisture, soil physical characteristics, vegetation, and microbial-mediated metabolic processes. The efficiency with which microorganisms use soil C regulates the balance between C storage in soil and the atmosphere. In this review, we discuss how microbial physiology and community assembly processes determine microbial growth rate and efficiency and, in turn, soil organic C cycling through the lens of community ecology. We introduce a conceptual framework cataloging life history (i.e., growth rate, resource acquisition, and stress tolerance) and assembly traits (i.e., competition, facilitation, and dispersal) that correspond with different growth efficiencies. We also compare how dominant mycorrhizal fungal type affects growth efficiency. We propose that further development and inclusion of specific community parameters in microbial-explicit Earth system models are needed for accurately predicting soil organic C responses to global change.
Abstract Soil organic matter decomposition and its interactions with climate depend on whether the organic matter is associated with soil minerals. However, data limitations have hindered global-scale analyses of mineral-associated and particulate soil organic carbon pools and their benchmarking in Earth system models used to estimate carbon cycle–climate feedbacks. Here we analyse observationally derived global estimates of soil carbon pools to quantify their relative proportions and compute their climatological temperature sensitivities as the decline in carbon with increasing temperature. We find that the climatological temperature sensitivity of particulate carbon is on average 28% higher than that of mineral-associated carbon, and up to 53% higher in cool climates. Moreover, the distribution of carbon between these underlying soil carbon pools drives the emergent climatological temperature sensitivity of bulk soil carbon stocks. However, global models vary widely in their predictions of soil carbon pool distributions. We show that the global proportion of model pools that are conceptually similar to mineral-protected carbon ranges from 16 to 85% across Earth system models from the Coupled Model Intercomparison Project Phase 6 and offline land models, with implications for bulk soil carbon ages and ecosystem responsiveness. To improve projections of carbon cycle–climate feedbacks, it is imperative to assess underlying soil carbon pools to accurately predict the distribution and vulnerability of soil carbon.
The combination of extended dry periods and high intensity rainfall, common in the southeastern US, leads to greater variability in soil moisture and consequently increases uncertainty to microbial processes pertinent to soil carbon (C) mineralization. However, field-based findings on soil moisture sensitivity to soil C cycling are very limited. Therefore, a field experiment was conducted in 2018 and 2019 on a soybean (Glycine max L.) cropland in the southeastern US with three soil moisture treatments: drought (simulated using rainout-shelter from June to October in each year), rainfed (natural precipitation), and irrigated (irrigation and precipitation). Soil respiration was measured weekly from May to November in both years. Soil samples were collected multiple times each year from 0–5, 5–15, and 15–30 cm depths to determine microbial biomass C (MBC), extractable organic C (EOC), hydrolytic enzyme activities, and fungal abundance. The cumulative respiration under drought compared to other treatments was lower by 32% to 33% in 2018 and 38% to 45% in 2019. Increased MBC, EOC, and fungal abundance were observed under drought than other treatments. Specific enzyme activity indicated fewer metabolically active microbes under drought treatment compared to rainfed and irrigated treatments. Also, maintenance of enzyme pool was observed under drought condition. These results provide critical insights on microbial metabolism in response to soil moisture variation and how that influences different pools of soil C under field conditions.
Soil organic carbon management has the potential to aid climate change mitigation through drawdown of atmospheric carbon dioxide. To be effective, such management must account for processes influencing carbon storage and re-emission at different space and time scales. Achieving this requires a conceptual advance in our understanding to link carbon dynamics from the scales at which processes occur to the scales at which decisions are made. Here, we propose that soil carbon persistence can be understood through the lens of decomposers as a result of functional complexity derived from the interplay between spatial and temporal variation of molecular diversity and composition. For example, co-location alone can determine whether a molecule is decomposed, with rapid changes in moisture leading to transport of organic matter and constraining the fitness of the microbial community, while greater molecular diversity may increase the metabolic demand of, and thus potentially limit, decomposition. This conceptual shift accounts for emergent behaviour of the microbial community and would enable soil carbon changes to be predicted without invoking recalcitrant carbon forms that have not been observed experimentally. Finally, functional complexity as a driver of soil carbon persistence suggests soil management should be based on constant care rather than one-time action to lock away carbon in soils.
Soil organic carbon (SOC) regulates terrestrial ecosystem functioning, provides diverse energy sources for soil microorganisms, governs soil structure, and regulates the availability of organically bound nutrients. Investigators in increasingly diverse disciplines recognize how quantifying SOC attributes can provide insight about ecological states and processes. Today, multiple research networks collect and provide SOC data, and robust, new technologies are available for managing, sharing, and analyzing large data sets. Here, we advocate that the scientific community capitalize on these developments to augment SOC data sets via standardized protocols. We describe why such efforts are important and the breadth of disciplines for which it will be helpful, and outline a tiered approach for standardized sampling of SOC and ancillary variables that ranges from simple to more complex. We target scientists ranging from those with little to no background in soil science to those with more soil-related expertise, and offer examples of the ways in which the resulting data can be organized, shared, and discoverable.
Microbial decomposition drives the transformation of plant-derived substrates into microbial products that form stable soil organic matter (SOM). Recent theories have posited that decomposition depends on an interaction between SOM chemistry with microbial diversity and resulting function. Here, we explicitly test these theories by coupling quantitative stable isotope probing and metabolomics to track the fate of 13C enriched substrates that vary in chemical composition as they are assimilated by microbes and transformed into new metabolic products in soil. We found that mycorrhizal-driven differences in forest nutrient economies (e.g., nutrient cycling, microbial competition) led to arbuscular mycorrhizal (AM) soils harboring greater micro8ial diversity than ectomycorrhizal (ECM) soils. When incubated with 13C enriched substrates, substrate type drove shifts in the identity of active decomposers and their metabolic products in the highly diverse AM soils. The decomposition pathways were more static in the less diverse, ECM soil. Importantly, the majority of these shifts were driven by taxa only present in the AM soil suggesting a strong link between microbial identity and specialized function. Collectively, these results highlight an important interaction between ecosystem-level processes and microbial diversity; whereby the identity and function of active decomposers impacts the composition of decomposition products that can form stable SOM.
Core-scale soil carbon fluxes are ultimately regulated by pore-scale dynamics of substrate availability and microbial access. These are constrained by physicochemical and biochemical phenomena (e.g. spatial access and hydrologic connectivity, physical occlusion, adsorption-desorption with mineral surfaces, nutrient and resource limitations). We conducted an experiment to determine how spatial access and resource limitations influence core-scale SOM mineralization, and how these are regulated by antecedent moisture conditions. Intact soil cores were incubated at field-moist vs. drought conditions, after which they were saturated from above (to simulate precipitation) or below (to simulate groundwater recharge). Soluble C (acetate) and N (nitrate) forms were added to some cores during the rewetting process to alleviate potential nutrient limitations. Respiration showed evidence of C-limitation, as C amendments increased the cumulative CO 2 evolved. Drought and rewetting increased soil respiration, and these soils also exhibited increased complex aromatic molecules in porewater. This newly available substrate appeared to alleviate nutrient limitations on respiration, because there were no further respiration increases with subsequent C and N amendments. We expected that respiration would be influenced by wetting direction, as simulated precipitation would mobilize C from the surface. However, as a main effect, this response was seen only in the C-amended soils, indicating that surface-C may not have been bioavailable. At the pore scale (porewater samples), compared to the baseline soils, drought and the C, N amendments caused a net loss of identified molecules when the soils were rewet from below, whereas wetting from above caused a net increase in identified molecules. This indicates that as soils were wet from below, the fresh inputs simulated the C-and N-limited microbial populations present deeper in the soil profile. Furthermore, our experiment highlights the complex and interactive role of antecedent moisture conditions, wetting direction, and resource limitations in driving core-scale C fluxes.
All data is collected from across 3 soil cores spanning a pH gradient at Point Reyes National Seashore, as part of a recent publication. The bulk data csv includes hygroscopic moisture content, soil pH, total C and N values, particle size distributions, cation exchange capacity and extractable cations. The STXM data package includes raw spectra data from scanning transmission X-ray microscopy C near-edge X-ray absorption fine structure spectroscopy analysis, extracted from STXM Image Reader analysis and then subsequently normalised in Athena (see details in paper). The data file also contains a bulk chemistry and mineralogy dataset, including total and trace element contents from 3 depths and mineral compositions as measured at BL 11-3 SSRL and semi-quantified in HighScore. Finally the final data file is calcium K-edge X-ray absorption near-edge structure spectroscopy (BL 4-3) and micro-XANES and micro-X-ray fluorescence (BL 14-3b) data.
Organo-mineral and organo-metal associations play an important role in the retention and accumulation of soil organic carbon (SOC). Recent studies have demonstrated a positive correlation between calcium (Ca) and SOC content in a range of soil types. However, most of these studies have focused on soils that contain calcium carbonate (pH > 6). To assess the importance of Ca-SOC associations in lower pH soils, we investigated their physical and chemical interaction in the grassland soils of Point Reyes National Seashore (CA, USA) at a range of spatial scales. Multivariate analyses of our bulk soil characterisation dataset showed a strong correlation between exchangeable Ca (Ca Exch ; 5–8.3 c.mol c kg –1 ) and SOC (0.6–4%) content. Additionally, linear combination fitting (LCF) of bulk Ca K-edge X-ray absorption near-edge structure (XANES) spectra revealed that Ca was predominantly associated with organic carbon across all samples. Scanning transmission X-ray microscopy near-edge X-ray absorption fine structure spectroscopy (STXM C/Ca NEXAFS) showed that Ca had a strong spatial correlation with C at the microscale. The STXM C NEXAFS K-edge spectra indicated that SOC had a higher abundance of aromatic/olefinic and phenolic C functional groups when associated with Ca, relative to C associated with Fe. In regions of high Ca-C association, the STXM C NEXAFS spectra were similar to the spectrum from lignin, with moderate changes in peak intensities and positions that are consistent with oxidative C transformation. Through this association, Ca thus seems to be preferentially associated with plant-like organic matter that has undergone some oxidative transformation, at depth in acidic grassland soils of California. Our study highlights the importance of Ca-SOC complexation in acidic grassland soils and provides a conceptual model of its contribution to SOC preservation, a research area that has previously been unexplored.
Abstract Quantifying the upper limit of stable soil carbon storage is essential for guiding policies to increase soil carbon storage. One pool of carbon considered particularly stable across climate zones and soil types is formed when dissolved organic carbon sorbs to minerals. We quantified, for the first time, the potential of mineral soils to sorb additional dissolved organic carbon (DOC) for six soil orders. We compiled 402 laboratory sorption experiments to estimate the additional DOC sorption potential, that is the potential of excess DOC sorption in addition to the existing background level already sorbed in each soil sample. We estimated this potential using gridded climate and soil geochemical variables within a machine learning model. We find that mid- and low-latitude soils and subsoils have a greater capacity to store DOC by sorption compared to high-latitude soils and topsoils. The global additional DOC sorption potential for six soil orders is estimated to be 107 $$\pm$$ ± 13 Pg C to 1 m depth. If this potential was realized, it would represent a 7% increase in the existing total carbon stock.